Joint pricing and ordering decisions for a loss-averse retailer with quantity-oriented reference point effect and demand uncertainty: a distribution-free approach
ISSN: 0368-492X
Article publication date: 23 December 2021
Issue publication date: 24 March 2023
Abstract
Purpose
This work examines the joint pricing and ordering (JPO) decisions for a loss-averse retailer with quantity-oriented reference point (RP) effect under demand uncertainty.
Design/methodology/approach
The demand is assumed to be uncertain with the mean and variance as the only known information. The prospect theory is used to model the retailer's expected utility. An expected utility maximization model in the distribution-free approach (DFA) is then developed. Using duality theory, the expected utility under the worst-case distribution is transformed into tractable piece-wise functions. To examine the effectiveness of the DFA in coping with the demand uncertainty, a stochastic programming model is developed and its solutions are used as benchmarks.
Findings
The proposed model and solution approach can effectively hedge against the demand uncertainty. The JPO decisions are significantly influenced by the LA coefficient and the reference level. The LA has a stronger influence than the reference level does on the expected utility. An excessive LA is detrimental while an appropriate reference level is beneficial to the retailer.
Practical implications
The results of this work are applicable to loss-averse retailers with the quantity-oriented RP when making JPO decisions with difficulty in predicting the demands.
Originality/value
The demand is assumed to be uncertain in this work, but a certain demand distribution is usually assumed in the existing literature. The DFA is used to study JPO decisions for the loss-averse retailer with quantity-oriented RP effect under the uncertain demand.
Keywords
Citation
Yu, Y., Qiu, R. and Sun, M. (2023), "Joint pricing and ordering decisions for a loss-averse retailer with quantity-oriented reference point effect and demand uncertainty: a distribution-free approach", Kybernetes, Vol. 52 No. 4, pp. 1294-1324. https://doi.org/10.1108/K-06-2021-0436
Publisher
:Emerald Publishing Limited
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